Browsing by Author "Yeiser, Emily Elizabeth"
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- Dairy Pipeline. October 2011Welsh, John; Yeiser, Emily Elizabeth; Petersson-Wolfe, Christina S. (Virginia Cooperative Extension, 2011-09-26)Discusses agricultural best management practices and environmental stewardship; and, monitoring animal activity to detect the onset of illness.
- The use of activity measures in combination with physiological factors as indicators of disease in dairy cattleYeiser, Emily Elizabeth (Virginia Tech, 2011-07-27)Animal activity, in combination with physiological factors, can be used for early disease detection in dairy cattle. An initial study determined the impact of flunixin meglumine (FM), a non-steroidal anti-inflammatory drug, on activity measures, dry matter intake (DMI) and milk production during experimentally induced Escherichia coli mastitis. A total of 24 primiparous and multiparous lactating dairy cows were challenged with E.coli 727 in one quarter. Of the 24 E.coli challenged animals, 12 were administered FM at 0.002 µg/45.5kg of body weight at the onset of clinical mastitis signs. The remaining 12 cows were untreated. An additional 11 cows were infused with 1 mL of sterile phosphate-buffered saline, and served as the control group. Activity measures were collected through the use of the Afi PedometerPlus© and HOBO® data loggers. E.coli mastitis altered animal activity and improvement in DMI and milk production of animals given FM was observed, thus providing evidence for the use of an NSAID as supportive therapy for mastitis. Additionally, activity and blood metabolites concentrations were collected and analyzed from periparturient dairy cows at the Virginia Tech Dairy Center to determine the likelihood of disease occurrence. Primiparous and multiparous Holstein, Jersey, and Crossbred dairy cows were monitored for daily rest bouts, rest duration, and rest time throughout the pre and postpartum periods. Activity measurements were collected using Afi PedometerPlus© pedometers. It was concluded that evaluation of activity changes, and comparison of deviations from healthy herdmates, could allow producers to utilize activity monitoring to proactively manage dairy herd health.